Design, implement, test, and continuously optimize end-to-end RAG pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.
Curate and develop high-quality datasets, using synthetic data generation for robust training and evaluation.
Rigorously evaluate LLM applications on metrics including correctness, latency, and hallucination.
Assist in the deployment of LLM-based applications, analyze user feedback, and contribute to iterative improvements.
Write clean, maintainable, and testable code following best practices.
Collaborate with cross-functional teams to integrate AI components into other systems.